1. Field of the Invention
This invention pertains generally to object modeling, and more particularly, to calculating mass property estimations for an object by using variable geometries to represent nonuniform densities and/or irregular shapes.
2. Description of Related Art
Computer modeling of objects such as humans, humanoid robots, animals (e.g., extinct animals), and the like, provides a powerful tool set for numerous applications. For example, human models can simulate the performance of dangerous activities prior to exposing a human to the activity. Humanoid robot models can simulate the performance of ordinary tasks, and be adjusted for improvements, prior to building a physical prototype. Also, extinct animal models can offer valuable insight for species that are impossible to observe in nature.
One difficultly with conventional computer modeling techniques lies in creating dynamic simulations of objects in motion. Because these models are virtual and are limited only by imagination, it is difficult to realistically access effects of physical characteristics, such as mass, volume, center of mass, inertia tensors, moments and the like. In other words, while it is currently possible to simulate a humanoid robot walking up a set of virtual stairs, there needs to be a way of simulating physical characteristics of this activity that would be presented in the real world. Inaccuracies can result in wasted efforts to build a prototype robot that cannot perform desired functions.
Current techniques used to model mass properties are problematic. Experimental methods attempt to directly measure properties from body segment specimens. For example, the photographic suspension method was used to determine the center of gravity of horse body parts. However, for this method, the specimen typically must be in a cadaveric state with all body segments disassembled. To overcome the need of specimens in cadaveric state, non-invasive approaches that use imaging technology such as CAT can be applied to virtually compute mass properties from image slices with tissue density maps. Unfortunately, this process is often expensive and time consuming. Another application develops human dynamic models for subject-specific simulation. Although one can use regression models, they do not account for specific variations in individual subjects because regression is based on statistical averages. In addition, the methods mentioned above require the existence of real specimens, which limits their application. Current geometric approaches typically require regular geometric shapes and uniform densities that are not accurate for reliable physical simulation.
Therefore, there is a need for a robust system and method of modeling objects using geometric shapes that can be varied to represent objects of nonuniform densities and/or irregular shape to provide accurate mass property estimation.